初始化项目，由ModelHub XC社区提供模型

Model: OmnicromsBrain/Eros_Scribe-10.7b-v3
Source: Original Platform

README.md

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+---
+base_model:
+- OmnicromsBrain/ToppyCox-10.7b
+- OmnicromsBrain/EverythingBagel-10.7b
+tags:
+- merge
+- mergekit
+- lazymergekit
+- OmnicromsBrain/ToppyCox-10.7b
+- OmnicromsBrain/EverythingBagel-10.7b
+---
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65c70c9e21d80a923d664563/sM8repDdiFzeJ6M0twE88.png)
+
+# Eros_Scribe-10.7b-v3
+
+
+This model was created for the purpose of writing NSFW Prose but it's also very good at RP.
+
+Versions 1 and 2 were the most verbose models I'd ever merged but they had lost most of their NSFW MoJo.
+I think I finally got the mix right as v3 returns some of the most NSFW I've seen...
+
+
+Over a dozen models and at least 25 dataset were involved in this merge. Eros_Scribe-10.7b-v3 is a merge of the following models:
+
+## OmnicromsBrain/EverythingBagel-DPO-7B
+
+### jondurbin/bagel-dpo-7b-v0.5
+
+### SanjiWatsuki/Silicon-Maid-7B
+
+chargoddard/loyal-piano-m7
+
+NeverSleep/Noromaid-7b-v0.2
+
+athirdpath/NSFW_DPO_vmgb-7b
+
+xDAN-AI/xDAN-L1-Chat-RL-v1
+
+## OmnicromsBrain/ToppyCox-7B
+
+### N8Programs/Coxcomb
+
+### Undi95/Toppy-M-7B
+
+openchat/openchat_3.5
+
+NousResearch/Nous-Capybara-7B-V1.9
+
+HuggingFaceH4/zephyr-7b-beta
+
+Undi95/zephyr-7b-beta-pippa-sharegpt
+
+Undi95/Nous-Capybara-7B-V1.9-120-Days
+
+Undi95/openchat_3.5-LimaRP-13B
+
+lemonilia/AshhLimaRP-Mistral-7B
+
+mistralai/Mistral-7B-v0.1
+
+
+## ⚡ Quantized Models
+
+Special thanks to **MRadermacher** for the **static** and **imatrix** quantized models
+
+**.GGUF** https://huggingface.co/mradermacher/Eros_Scribe-10.7b-v3-GGUF
+
+**IMatrix** https://huggingface.co/mradermacher/Eros_Scribe-10.7b-v3-i1-GGUF
+
+
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "OmnicromsBrain/Eros_Scribe-10.7b-v3"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```